EVA-1 Functions as an UNC-40 Co-receptor to Enhance Attraction to the MADD-4 Guidance Cue in Caenorhabditis elegans
Bibliographic record
Abstract
We recently discovered a secreted and diffusible midline cue called MADD-4 (an ADAMTSL) that guides migrations along the dorsoventral axis of the nematode Caenorhabditis elegans. We showed that the transmembrane receptor, UNC-40 (DCC), whose canonical ligand is the UNC-6 (netrin) guidance cue, is required for extension towards MADD-4. Here, we demonstrate that MADD-4 interacts with an EVA-1/UNC-40 co-receptor complex to attract cell extensions. EVA-1 is a conserved transmembrane protein with predicted galactose-binding lectin domains. EVA-1 functions in the same pathway as MADD-4, physically interacts with both MADD-4 and UNC-40, and enhances UNC-40's sensitivity to the MADD-4 cue. This enhancement is especially important in the presence of UNC-6. In EVA-1's absence, UNC-6 interferes with UNC-40's responsiveness to MADD-4; in UNC-6's absence, UNC-40's responsiveness to MADD-4 is less dependent on EVA-1. By enabling UNC-40 to respond to MADD-4 in the presence of UNC-6, EVA-1 may increase the precision by which UNC-40-directed processes can reach their MADD-4-expressing targets within a field of the UNC-6 guidance cue.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".